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The key highlights from the Oxipit team at this year's UKIO conference, highlighting the pivotal discussions on autonomous reporting in radiology.

Oxipit further expands commercial availability of its solutions via partnership with deepc. This collaboration will integrate Oxipit’s advanced AI solutions - ChestLink, ChestEye, and ChestEye Quality - into the deepcOS platform, delivering effortless access to Oxipit solutions directly within existing Healthcare IT systems, with just one simple integration.

Oxipit, a leading AI radiology solutions provider, has appointed senior health tech executive, Peter Corscadden, as Chief Executive Officer to strengthen its global footprint.

A research paper comparing the performance of commercially available AI algorithms was published in the Radiology journal. While multiple commercial artificial intelligence (AI) products for assessing radiographs exist in the market, comparable performance data for these algorithms is limited.

Blackford, the pioneering strategic radiology AI platform and solutions provider, today announced a partnership with AI medical imaging company Oxipit. The agreement will bring innovative Oxipit’s chest x-ray products to Blackford’s enterprise AI platform.

Leiden University Medical Center (The Netherlands) expands cooperation with AI medical imaging company Oxipit by deploying the latest Oxipit product - AI quality assurance tool for CT Pulmonary Embolism (PE). The LUMC deployment was facilitated through the radiology imaging solution by Sectra and its integration capabilities.

Last April Oxipit took the medical imaging world by storm. The medical imaging company received a CE Class IIb certificate for the first autonomous AI imaging application ChestLink. Learn about the team who made this innovation possible.

A study led by Louis Lind Plesner, MD comparing the performance of four commercial AI CXR tools was published in the Radiology Journal, with Oxipit ChestEye among the ones tested. The study evaluated AI algorithm performance for detecting airspace disease, pneumothorax, and pleural effusion.

A study by researchers at Mahajan Imaging and CARPL.ai was conducted to evaluate the performance of diagnostic AI tools for quality assurance. The study found that nearly 1% of chest radiographs included clinically significant diagnostic mistakes, which were identified by Oxipit Quality AI software. The study was presented at the ECR2023 annual meeting earlier in March.

An AI tool can accurately identify normal and abnormal chest X-rays in a clinical setting, according to a study published in Radiology. The tool may greatly alleviate the heavy workload experienced by radiologists globally.